Threshold Parameter Research Articles

A phase field model with modified volumetric-deviatoric decomposition for the mixed-mode fracture of rock

Recent attempts of phase field models to simulate rock fracture problems have been regarded as fruitful, owing to their powerful crack characterization capability. However, existing phase field models still exhibit limitations in simulating quasi-coplanar shear cracks and related coalescence patterns that often occur in rock failure. In this study, we propose a novel phase field model to simulate the mixed-mode fracture, in which a modified volumetric-deviatoric decomposition that combines the advantages of the volumetric-deviatoric decomposition and the spectral decomposition is conducted to distinguish between tensile, tensile-shear, and compressive-shear fractures; to reduce unrealistic damage in the area outside the crack trajectory, a threshold parameter is introduced into the degradation function to control whether the related energy participates in damage evolution; and the hybrid formulation is employed to efficiently and robustly solve the displacement and phase fields alternately. The feasibility of the proposed phase field model is first validated by a benchmark example. Next, the application of this model to the simulations of different rock specimens under uniaxial compression reveals a better agreement with experimental observations than previous simulation results, demonstrating an advancement over existing phase field models.

Automating thresholds in probabilistic linkage

ObjectiveThe Office for National Statistics aim is to create a platform containing a variety of datasets interlinked via data spines. The resource burden linking this many datasets is high, and so research to maximise automation is a key aim of the platform’s methodology. Probabilistic linkage is a standard linkage technique that utilises clerical resolution – a very costly process – to find acceptance threshold parameters. Here, we present research into automating threshold assignment. Every admin dataset is different, causing the probabilistically matched pairs scores to change, a set threshold cannot be used. Instead, a data-informed threshold must be set. ApproachA gold standard linked dataset was linked through Fellegi-Sunter, stopping at the point of finding the probabilistic threshold. To find the threshold, graphs plotting the number of records at each rounded score were created and reviewed, specifically looking at the spread of gold standard links, deterministic links, unique and non-unique probabilistic links. This review suggested a method of threshold assignment that provides multiple quality levels: a high-precision threshold, and a high-recall threshold. This presentation will showcase these graphs and explain how the two thresholds are calculated. The 2021 Census is one dataset linked within the gold standard linked dataset. The 2021 Census has high quality and relatively clean data, but is likely not representative of administrative data needed in the data platform. Therefore, next steps are testing this method on other datasets with a variety of quality, characteristics, and types.

Fake Base Station Detection and Link Routing Defense

Fake base stations comprise a critical security issue in mobile networking. A fake base station exploits vulnerabilities in the broadcast message announcing a base station’s presence, which is called SIB1 in 4G LTE and 5G NR, to get user equipment to connect to the fake base station. Once connected, the fake base station can deprive the user of connectivity and access to the Internet/cloud. We discovered that a fake base station can disable the victim user equipment’s connectivity for an indefinite period of time, which we validated using our threat prototype against current 4G/5G practices. We designed and built a defense scheme which detects and blacklists a fake base station and then, informed by the detection, avoids it through link routing for connectivity availability. For detection and blacklisting, our scheme uses the real-time information of both the time duration and the number of request transmissions, the features of which are directly impacted by the fake base station’s threat and which have not been studied in previous research. Upon detection, our scheme takes an active measure called link routing, which is a novel concept in mobile/4G/5G networking, where the user equipment routes the connectivity request to another base station. To defend against a Sybil-capable fake base station, we use a history–reputation-based link routing scheme for routing and base station selection. We implemented both the base station and the user on software-defined radios using open-source 5G software (srsRAN v23.10 and Open5GS v2.6.6) for validation. We varied the base station implementation to simulate legitimate vs. faulty but legitimate vs. fake and malicious base stations, where a faulty base station notifies the user of the connectivity disruption and releases the session, while a fake base station continues to hold the session. We empirically analyzed the detection and identification thresholds, which vary with the fake base station’s power and the channel condition. By strategically selecting the threshold parameters, our scheme provides zero errors, including zero false positives, to avoid blacklisting a temporarily faulty base station that cannot provide connectivity at the time. Furthermore, our link routing scheme enables the base station to switch in order to restore the connectivity availability and limit the threat impact. We also discuss future directions to facilitate and encourage R&D in securing telecommunications and base station security.

Global stability for age-structured heroin model with general nonlinear incidence rate and time delay

In this article, we consider a mathematical model on the consumption of Heroin, it is an epidemiological model describing the interactions between heroin consumers and the rest of the population. The model is a system of differential equations with delay, integro-differential equations and partial differential equations. The first equation describes the evolution of healthy individuals, who do not consume Heroin. The second equation describes the evolution of consumer individuals, and in the last equation we find the evolution of individuals under treatment, so that they become healthy. In this work, we are interested in the qualitative study of the system considered. We examine the effects of a nonlinear incidence function with lag on the dynamics of an age-of-infection structured Heroin consumption model in the framework of mathematical epidemiology. We prove that incorporating the lag into the model does not change the asymptotic behavior of its equilibrium states. By defining the basic reproduction number R0 as a critical threshold parameter, we show that if R0 < 1, the disease-free equilibrium (DFE) is globally stable regardless of the lag τ. Conversely, if R0 < 1, the model exhibits an endemic equilibrium (EE) that remains locally and globally asymptotically stable for any lag τ. Our results highlight the robustness of the equilibrium stability in response to variations in the lag and provide important insights into the long-term dynamics of Heroin consumption, providing a clearer understanding of the conditions under which epidemic outcomes are stable or unstable.

Towards Optimising the Derivation of Phenological Phases of Different Crop Types over Germany Using Satellite Image Time Series

Operational crop monitoring applications, including crop type mapping, condition monitoring, and yield estimation, would benefit from the ability to robustly detect and map crop phenology measures related to the crop calendar and management activities like emergence, stem elongation, and harvest timing. However, this has proven to be challenging due to two main issues: first, the lack of optimised approaches for accurate crop phenology retrievals, and second, the cloud cover during the crop growth period, which hampers the use of optical data. Hence, in the current study, we outline a novel calibration procedure that optimises the settings to produce high-quality NDVI time series as well as the thresholds for retrieving the start of the season (SOS) and end of the season (EOS) of different crops, making them more comparable and related to ground crop phenological measures. As a first step, we introduce a new method, termed UE-WS, to reconstruct high-quality NDVI time series data by integrating a robust upper envelope detection technique with the Whittaker smoothing filter. The experimental results demonstrate that the new method can achieve satisfactory performance in reducing noise in the original NDVI time series and producing high-quality NDVI profiles. As a second step, a threshold optimisation approach was carried out for each phenophase of three crops (winter wheat, corn, and sugarbeet) using an optimisation framework, primarily leveraging the state-of-the-art hyperparameter optimization method (Optuna) by first narrowing down the search space for the threshold parameter and then applying a grid search to pinpoint the optimal value within this refined range. This process focused on minimising the error between the satellite-derived and observed days of the year (DOY) based on data from the German Meteorological Service (DWD) covering two years (2019–2020) and three federal states in Germany. The results of the calculation of the median of the temporal difference between the DOY observations of DWD phenology held out from a separate year (2021) and those derived from satellite data reveal that it typically ranged within ±10 days for almost all phenological phases. The validation results of the detection of dates of phenological phases against separate field-based phenological observations resulted in an RMSE of less than 10 days and an R-squared value of approximately 0.9 or greater. The findings demonstrate how optimising the thresholds required for deriving crop-specific phenophases using high-quality NDVI time series data could produce timely and spatially explicit phenological information at the field and crop levels.

Learning-based dynamic pricing strategy with pay-per-chapter mode for online publisher with case study of COL

We consider how to make dynamic pricing decision for Chinese Online (COL) at T time-points, an online publisher that allow authors to sell their ongoing book projects. Instead of paying for a book, readers pay for each chapter (pay-per-chapter mode) of the ongoing book project. This mode allows readers to pay for as many chapters as they want without taking the risk that the releasing of new chapters might be delayed or stopped. Despite of the dynamics of chapter-by-chapter released of COL products, the fixed pricing strategy (FPS) does not make fully use of the reading data generated by releasing chapters of the ongoing book. We propose a learning-based dynamic pricing strategy (LDPS) that exploits the newly information to maximize cumulative revenue for the publisher. The LDPS captures the ever changing features of readers. It employs the Thompson sampling method to balance the exploration of investigating different prices sufficiently with the exploitation of settling on the optimal price. Taking COL as a case study and implementing our strategy in the context of the aforementioned real-life data set, we show that LDPS outperform several classical strategies such as Greedy, Prior-Free TS and Prior-Given TS, and average revenue of LDPS is increased by 0.5 % average per time-point compared to the publisher's historical decisions. We also provide some management implications for the COL publisher by analyzing the pricing range of different genres of books and the choice of the exploration threshold parameter.

Multiple Parameter Replica Exchange Gaussian Accelerated Molecular Dynamics for Enhanced Sampling and Free Energy Calculation of Biomolecular Systems.

This study introduces a novel method named multiple parameter replica exchange Gaussian accelerated molecular dynamics (MP-Rex-GaMD), building on the Gaussian accelerated molecular dynamics (GaMD) algorithm. GaMD enhances sampling and retrieves free energy information for biomolecular systems by adding a harmonic boost potential to smooth the potential energy surface without the need for predefined reaction coordinates. Our innovative approach advances the acceleration power and energetic reweighting accuracy of GaMD by incorporating a replica exchange algorithm that enables the exchange of multiple parameters, including the GaMD boost parameters of force constant and energy threshold, as well as temperature. Applying MP-Rex-GaMD to the three model systems of dialanine, chignolin, and HIV protease, we demonstrate its superior capability over conventional molecular dynamics and GaMD simulations in exploring protein conformations and effectively navigating various biomolecular states across energy barriers. MP-Rex-GaMD allows users to accurately map free energy landscapes through energetic reweighting, capturing the ensemble of biomolecular states from low-energy conformations to rare high-energy transitions within practical computational time scales.

Dynamic event-driven optimal consensus control for state-constrained multiagent zero-sum differential graphical games

In this paper, a dynamic event-driven optimal control scheme is proposed for the zero-sum differential graphical games in nonlinear multiagent systems with full-state constraints. Initially, to address the dual demands of optimality and state constraints, a set of system transformation functions are introduced to satisfy the state constraints of the agents. Then, by applying the principle of differential game theory, the distributed optimal control problem affected by external disturbances is formulated as a zero-sum differential graphical game, and the performance index function related to neighbor informations and disturbances is designed for each follower. Afterwards, to enhance the utilization of communication resource, a novel dynamic event-triggered mechanism characterized by a dynamic threshold parameter and an auxiliary dynamic variable is developed, which not only exhibits greater flexibility but also diminishes the frequency of triggers. Furthermore, the approximate optimal control strategies are obtained by employing an event-driven adaptive dynamic programming algorithm. Ultimately, a simulation example is presented to verify the applicability of the proposed control approach.

Epidemiological Model of the Regional Distribution and Analysis of Hepatitis B in Ghana: A Sub-Saharan African Country

Hepatitis B (HB) is a global public health burden which has impacted economies of many countries, particularly in sub-Saharan Africa. The effect is worse where there is lack of definite information regarding policy direction and capacity towards implementing interventions to control the transmission and spread of the infection. In this study, a SEIR deterministic compartmental model and a hybrid optimisation method for parameter estimation, similar to that of Awuah-Mensah et al. (2022), were used to analyse the regional distribution of HB in Ghana, a sub-Saharan African country. The regional epidemiological threshold parameters [Formula: see text] and herd immunity threshold parameters [Formula: see text] computed based on the estimated parameters for each of the regions ranged from a minimum of [Formula: see text] for Volta region in the southeast to a maximum of [Formula: see text] for Upper West region in the northwest of Ghana. These values of [Formula: see text] and [Formula: see text] indicated that HB persists in Ghana and the transmission and spread and the associated burden were found to generally increase from south to north of the country. Based on the estimated parameters, only Western region recorded a recovery rate of [Formula: see text]. The remaining nine regions recorded zero recovery rates. The trend of transmission and spread of the infection was also found to be positively related to poverty and health sector inequalities across the regions of the country.

Likelihood-Ratio-Based Confidence Intervals for Multiple Threshold Parameters

Abstract This paper proposes the inversion of likelihood ratio tests for the construction of confidence intervals for multiple threshold parameters. Using Monte Carlo simulations, conservative likelihood-ratio-based confidence intervals are shown to exhibit empirical coverage rates at least as high as nominal levels for all threshold parameters, while still being informative in the sense of only including relatively few observations in each confidence interval. These findings are robust to the magnitude of the threshold effect, the sample size and the presence of serial correlation. Applications to existing models with multiple thresholds for U.S. real GDP growth and for the wage Phillips curve demonstrate how the proposed approach is empirically relevant to make inferences about the uncertainty of threshold estimates.

Deciphering the enigma of Lassa virus transmission dynamics and strategies for effective epidemic control through awareness campaigns and rodenticides

This study aims to formulate a mathematical framework to examine how the Lassa virus spreads in humans of opposite genders. The stability of the model is analyzed at an equilibrium point in the absence of the Lassa fever. The model’s effectiveness is evaluated using real-life data, and all the parameters needed to determine the basic reproduction number are estimated. Sensitivity analysis is performed to pinpoint the crucial parameters significantly influencing the spread of the infection. The interaction between threshold parameters and the basic reproduction number is simulated. Control theory is employed to devise and evaluate strategies, such as awareness campaigns, advocating condom usage, and deploying rodenticides to reduce the possibility of virus transmission efficiently.

Relationship between fatigue crack threshold K max,th and K 1SCC

Abstract This article describes the relationship that relates the static threshold parameter of K 1SCC (at ∼10−10 m/s) to ΔK th and K max,th (at ∼10−10 m/cycle) under fatigue load at high R-ratio like R = 0.85. At these high R-ratios (>0.75), applied K max > K 1SCC and the fracture path has a larger component of static fracture. 5083 Al alloy is adapted as an example to demonstrate this relationship at room temperature their relationship with and without GB-β anodic precipitates in inert and a 3.5 % NaCl solution environments. We are interested in the mechanical cyclic ΔK th and K max,th and quasi-static K ISCC driving forces affecting the damage in the presence of a chemical environment due to anodic dissolution of the GB-β precipitates. Detailed discussions involve how these parameters are interrelated.

A conformable mathematical model of Ebola Virus Disease and its stability analysis

Ebola Virus Disease (EVD) is a viral hemorrhagic fever that affects humans and other primates. It is characterized by rapid virus spread in a short period of time. The disease has the potential to spread to many different regions of the world. In this paper, we have developed a modified mathematical model of the Ebola virus, adding the quarantine population as a control strategy. The quarantine population F and parameters ρ3 represent the rate at which individuals enter the quarantine compartment, which is vital in controlling the virus spread within society. The conformable derivatives have been applied to the modified model to observe the behavior of individuals for fractional derivative values between 0.7 and 1. For a modified model, the threshold parameter (R0) has been determined using the Next-Generation Matrix (NGM) method. We have checked local and global stability at a disease-free equilibrium point using Routh-Herwitz (RH) criteria and Castillo-Chavez, respectively. Numerical results obtained through the Fourth-Order Runge Kutta Method (RK4) demonstrate, a decrease in the virus transmission rate after following the implementation of the quarantine strategy.

Distributed Dynamic Event-Triggered Leader-Following Consensus for Nonlinear Multiagent Systems Over Fading Channel.

This article investigates the leader-following consensus problem of discrete-time nonlinear multiagent systems (MASs) over fading channels. With the consideration of the transmission among followers maybe affected by the fading networks, the nonidentical fading channels model is constructed. To reduce the transmission network burden, the dynamical event-triggered mechanism (DETM) is developed. Different from most of existing event-triggered strategies, the threshold parameter in the developed dynamical event-triggering condition is dynamically adjusted according to a dynamic rule. Based on the DETM, a distributed consensus control protocol is designed under fading channels. Then, sufficient criteria are provided to ensure that MASs can achieve the leaser-following consensus, and satisfy the H∞ performance index in the presence of fading channels. The desired controller parameters can be derived in terms of solutions of matrix inequalities that are lightly solvable. In the end, simulation results show that the designed dynamical event transmission policy is capable of diminishing communication burden more promptly and effectively than some existing ones.

The Predictive Role of Metabolic Volume Segmentation Compared to Semiquantitative PET Parameters in Diagnosis of LVAD Infection using [18F]FDG Imaging

PurposeLeft ventricular assisting device (LVAD) is a vital mechanical circulatory assist device for patients with end-stage heart disease, serving as either a bridge to transplantation or palliative destination therapy. Yet device infection represents a major lethal complication, warranting a multi-step, complex therapy approach including an urgent device exchange or heart transplantation. Still, timely diagnosis of site and extent of VAD-specific infection for a proper therapy planning poses challenges in regular clinical care. This single-center, retrospective study aimed to evaluate the impact of volumetric PET parameters with different thresholding compared to semiquantitative PET parameters for accurate diagnosis of VAD-specific infection.ProceduresSeventeen patients (1 female, 16 males; mean age 57 ± 11 years) underwent [18F]FDG imaging for suspected VAD-specific infection between April 2013 and October 2023. Various metabolic and volumetric PET parameters with different thresholding were collected for specific LVAD components including driveline entry point, subcutaneous driveline, pump pocket, inner cannula and outflow tract. Microbiology and clinical follow-up were used as the final diagnosis standard.ResultsNine of eleven patients with VAD-specific infection underwent urgent heart transplantation, and one had a surgical revision of LVAD. Two patients had non-VAD specific infections, and two had non-VAD related infections. Metabolic burden determination using a fixed absolute threshold provided the best outcome compared to relative thresholding or other metabolic SUV parameters. The total metabolic tumor volume (MTV) cutoff value was 9.3 cm3, and the corresponding sensitivity, specificity, accuracy, and AUC were 90.0%, 71.43%, 82.5%, and 0.814 (95% CI 0.555–0.958), respectively. The total lesion glycolysis (TLG) was 30.6, and the corresponding sensitivity, specificity, accuracy, and AUC were 90.0%, 71.4%, 82.5%, and 0.829 (95% CI 0.571–0.964), respectively.ConclusionsVolumetric PET parameters with fixed absolute thresholding appear to be a valuable auxiliary tool in the evaluation of [18F]FDG imaging to enhance the diagnostic accuracy of VAD-specific infection.

A Mathematical Model for the Co-infection Dynamics of Pneumocystis Pneumonia and HIV/AIDS with Treatment

The control of opportunistic infections among HIV infected individuals should be one of the major public health concerns in reducing mortality rate of individuals living with HIV/AIDS. In this study a deterministic co-infection mathematical model is developed to provide a quantification of treatment at each contagious stage against Pneumocystis Pneumonia (PCP) among HIV infected individuals on ART. The goal is to minimize the co-infection burden by putting the curable PCP under control. The disease-free equilibria for the HIV/AIDS sub-model, PCP sub-model and the co-infection model are shown to be locally asymptotically stable when their associated disease threshold parameter is less than a unity. By use of suitable Lyapunov functions, the endemic equilibria corresponding to HIV/AIDS and PCP sub-models are globally asymptotically stable whenever the HIV/AIDS related basic reproduction number <I>R</I><sub>0<I>H</I></sub> and the PCP related reproduction number <I>R</I><sub>0<I>P</I></sub> are respectively greater than a unity. The sensitivity analysis results implicate that the effective contact rates are the main mechanisms fueling the proliferation of the two diseases and on the other hand treatment efforts play an important role in reducing the incidence. The model numerical results reveal that PCP carriers have a considerable contribution in the transmission dynamics of PCP. Furthermore, treatment of PCP at all contagious phases significantly reduces the burden with HIV/AIDS and PCP co-infection.

AUTO-TUNE: selecting the distance threshold for inferring HIV transmission clusters.

Molecular surveillance of viral pathogens and inference of transmission networks from genomic data play an increasingly important role in public health efforts, especially for HIV-1. For many methods, the genetic distance threshold used to connect sequences in the transmission network is a key parameter informing the properties of inferred networks. Using a distance threshold that is too high can result in a network with many spurious links, making it difficult to interpret. Conversely, a distance threshold that is too low can result in a network with too few links, which may not capture key insights into clusters of public health concern. Published research using the HIV-TRACE software package frequently uses the default threshold of 0.015 substitutions/site for HIV pol gene sequences, but in many cases, investigators heuristically select other threshold parameters to better capture the underlying dynamics of the epidemic they are studying. Here, we present a general heuristic scoring approach for tuning a distance threshold adaptively, which seeks to prevent the formation of giant clusters. We prioritize the ratio of the sizes of the largest and the second largest cluster, maximizing the number of clusters present in the network. We apply our scoring heuristic to outbreaks with different characteristics, such as regional or temporal variability, and demonstrate the utility of using the scoring mechanism's suggested distance threshold to identify clusters exhibiting risk factors that would have otherwise been more difficult to identify. For example, while we found that a 0.015 substitutions/site distance threshold is typical for US-like epidemics, recent outbreaks like the CRF07_BC subtype among men who have sex with men (MSM) in China have been found to have a lower optimal threshold of 0.005 to better capture the transition from injected drug use (IDU) to MSM as the primary risk factor. Alternatively, in communities surrounding Lake Victoria in Uganda, where there has been sustained heterosexual transmission for many years, we found that a larger distance threshold is necessary to capture a more risk factor-diverse population with sparse sampling over a longer period of time. Such identification may allow for more informed intervention action by respective public health officials.

Research on approximate optimal energy management and multi-objective optimization of connected automated range-extended electric vehicle

In order to attain the optimal allocation of energy between auxiliary power unit (APU) and battery of the connected automated range-extended electric vehicle, from a multi-scale perspective, an Approximate Optimal Energy Management Strategy (AOEMS) has been proposed. Firstly, a composite determination method was designed based on prediction and parameter identification to divide the operating condition types, which could be as an operating condition prediction and feed forward control method to determine the approximate optimal power distribution between APU and battery. This method keeps APU operating at the optimal operating point/area as much as possible without predicting the accurate vehicle speed sequence. Then, an adaptive method based on V2X information was used to adjust the key threshold parameters in real-time using a fuzzy logic controller which reduces the algorithm complexity with prediction and division of the operating conditions types, which has significantly improved the robustness and overall performance of the optimization. Finally, the simulation and experimental results thoroughly indicated that the proposed AOEMS can better balance the performances, as anticipated, enhancing economy, reducing emissions, and extending battery lifewere effectively maintained in equilibrium.

Mathematical model of mosquito population dynamics with constants and periodic releases of Wolbachia-infected males

In this article, we propose three mathematical models of mosquito dynamics. The first model describes the dynamics of wild mosquitoes in combination with mechanical control and larvicide. For this model, we derive a threshold parameter N , called the basic number of offspring, and show that the trivial equilibrium is globally asymptotically stable when N ≤ 1 , while if N > 1 , the non-trivial equilibrium is globally asymptotically stable. In the second model, we evaluated a constant release of Wolbachia-infected males in the wild mosquito population. Our analysis identified a critical threshold for releasing Wolbachia-infected male mosquitoes M i crit to reduce or eliminate the wild mosquito population. In the third model, we assessed wild mosquito dynamics by periodically releasing Wolbachia-infected male mosquitoes. The analysis of this model produced two thresholds, T ∗ the threshold on the release period and Λ ∗ the threshold on the release quantity. The existence of trivial periodic solutions is obtained, and the corresponding local and global stability conditions are proved by Floquet's theory and Lyapunov's stability theorem, respectively. We also prove the existence conditions for non-trivial periodic solutions and their local stability. Finally, we perform some numerical simulations to illustrate our theoretically pertinent results.

Exploring threshold dynamics of a behavioral epidemic model featuring two susceptible classes and second-order jump–diffusion

Understanding and modeling behavioral changes during epidemic outbreaks is crucial for devising effective public health interventions. In this paper, we introduce an enhanced behavioral epidemic model that integrates novel elements to better capture real-world phenomena. Our model incorporates logistic growth as a recruitment rate, reflecting the population’s intrinsic growth constraints. Additionally, we consider two incidence rates to account for varying transmission dynamics. To extend the model’s applicability, we introduce perturbations through second-order jump–diffusion processes, allowing for abrupt changes in population dynamics. We define a threshold parameter based on the properties of an auxiliary system, which distinguishes between the existence of a unique stationary distribution and stochastic extinction. Through numerical simulations, we validate our theoretical findings and demonstrate the impact of nonlinear noise on the model dynamical behavior.